Hypotheses Testing
Hypothesis testing is a statistical method that is used to determine whether there is enough evidence in a sample of data to infer that a certain condition is true for the entire population. It involves formulating a null hypothesis, which is a statement that assumes there is no significant difference between two or more sets of data, and an alternative hypothesis, which is a statement that assumes there is a significant difference between the sets of data. The null hypothesis is then tested against the alternative hypothesis using statistical tests such as t-tests, ANOVA, and chi-square tests. The results of these tests are used to determine whether the null hypothesis can be rejected or not. Hypothesis testing is an important tool in data science and is used to make decisions based on data analysis.
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